{"id":"W4386964123","doi":"10.1101/2023.09.20.558484","title":"PCR-based amplification of a <i>cox1</i> mini-DNA barcode gene from feces: A non-invasive molecular technique to identify environmental DNA samples of maritime shrew ( <i>Sorex maritimensis</i> )","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University; York University","funders":"","keywords":"Shrew; Environmental DNA; Biology; Amplicon; Feces; DNA barcoding; Sorex; Zoology; DNA extraction; Habitat; Nova scotia; Polymerase chain reaction; Ecology; Fishery; Gene; Genetics; Biodiversity; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004099104,0.0006603508,0.0003124826,0.0007555568,0.0002460247,0.0003602516,0.0004575882,0.000423431,0.001016266],"category_scores_gemma":[0.001086053,0.0003324537,0.0003640033,0.0003461856,0.0003881403,0.0002357244,0.0002476625,0.0005198895,0.000924897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276652,"about_ca_system_score_gemma":0.0005369009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003974006,"about_ca_topic_score_gemma":0.01360275,"domain_scores_codex":[0.9992926,0.00008870887,0.0000525498,0.0002663941,0.0002211589,0.00007849357],"domain_scores_gemma":[0.9990402,0.0002099181,0.0003268365,0.00005718802,0.000290545,0.00007534593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004714687,0.00004046863,0.004583979,0.00009862161,0.000005649685,0.00006153921,0.0000951515,0.00004317809,0.9909746,0.00003572737,0.0000554148,0.00395848],"study_design_scores_gemma":[0.00002627026,0.000873037,0.1047346,0.0001097563,0.0000648653,0.0009236005,0.0004059601,0.003205427,0.8842934,0.00006209089,0.005272489,0.00002859139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8631002,0.001022637,0.127812,0.0001587148,0.000115789,0.001239044,0.00311414,0.0005238205,0.002913811],"genre_scores_gemma":[0.6911477,0.001256529,0.2922394,0.0004040013,0.00004821009,0.000971923,0.006533291,0.0001768211,0.007222189],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003974006,"threshold_uncertainty_score":0.007901788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640738614181695,"score_gpt":0.2144686106390966,"score_spread":0.1980612244972796,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}